Q-omics provides the consensus-scored SPRY2 profile across patient tissues and cancer cell-line models. SPRY2 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SPRY2 is differentially expressed in 16, with the highest sampling consensus in KICH. Additionally, SPRY2 RNA expression shows 20,109 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, KICH, and ACC as cancer lineages where SPRY2 shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for SPRY2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SPRY2 survival associations across molecular data types. SPRY2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (1) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SPRY2 RNA expression–survival associations across cancer types. High SPRY2 expression shows unfavorable associations in ACC and LGG, but favorable associations in KIRC, UCEC, MESO and SKCM. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for SPRY2 RNA expression.
This table summarizes SPRY2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 3. The strongest signals are observed in KICH for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for SPRY2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SPRY2 shows lower tumor expression in KICH, LUSC, LUAD, BLCA, KIRP and BRCA. The KICH box plot shows higher SPRY2 RNA expression in normal versus tumor tissue (log2 FC = −2.607, t-test p < 0.001).
This table shows molecular features associated with SPRY2 in patient tissues and cancer cell lines. In patient samples, SPRY2 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, SPRY2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in STOMACH and UPPER_AERODIGESTIVE_TRACT.
